Buffer allocation is a critical issue in the design stage of manufacturing systems, as buffer capacities may have a great impact on system performance. In this paper, we consider the problem of minimizing the total bu...
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Buffer allocation is a critical issue in the design stage of manufacturing systems, as buffer capacities may have a great impact on system performance. In this paper, we consider the problem of minimizing the total buffer capacity of a flow line to achieve a desired production rate. A recursive optimization approach is proposed to solve the problem in large production lines. Instead of optimizing a long line directly, the proposed approach decomposes it into two sub-lines, optimizes them recursively, and combines their solutions to find the optimal buffer distribution of the original line. Two different recursive algorithms are developed and their performance is demonstrated by comparing them with a gradient search algorithm. The numerical results show that the recursive algorithms are almost as accurate as the gradient algorithm, but much more efficient, especially for large production lines.
Two dimensional Fredholm integral equation of the second kind (2DF-II) on a bounded domain D is regarded as the problem with characteristic values. A two dimensional function-valued Pade-type approximation(2DFPTA) is ...
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Two dimensional Fredholm integral equation of the second kind (2DF-II) on a bounded domain D is regarded as the problem with characteristic values. A two dimensional function-valued Pade-type approximation(2DFPTA) is defined. Its error formulas and convergence theorems are presented. To obtain higher order 2DFPTA, a determinantal expression and its recursive algorithm are given. In the end three numerical examples are tested, where one on the unit triangle of vertices (0, 0), (0, 1), (1, 0) and the other two on the square. The testing results show that 2DFPTA method is more accurate. (C) 2014 Elsevier Inc. All rights reserved.
In this brief, a new method for computing the matrix polynomial is proposed. The comparison demonstrates that this is the most efficient technique at the moment, Furthermore we argue that the approach is optimal in th...
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In this brief, a new method for computing the matrix polynomial is proposed. The comparison demonstrates that this is the most efficient technique at the moment, Furthermore we argue that the approach is optimal in the framework of the discussed algorithms. The algorithm is recursive and it can be viewed as resulting from a new number system.
Based on the image theory and addition theorem of spherical vector wave functions, a multiple-reflection solution is described for the electromagnetic scattering by a buried sphere. An iterative process is introduced ...
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Based on the image theory and addition theorem of spherical vector wave functions, a multiple-reflection solution is described for the electromagnetic scattering by a buried sphere. An iterative process is introduced to obtain the scattered field by enforcing the boundary conditions at the plane interface between free space and an isotropic medium and the spherical surface of a dielectric sphere buried in the isotropic medium. Numerical results for the scattered fields are provided and compared with those obtained by the commercial software FEKO. A good agreement is observed, which verifies the presented formulation.
An account is given of prevalent misconceptions concerning the computational and theoretical testing of matrices for positive semidefiniteness. A simple counterexample indicates that the recently proposed partitioned ...
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An account is given of prevalent misconceptions concerning the computational and theoretical testing of matrices for positive semidefiniteness. A simple counterexample indicates that the recently proposed partitioned test for this property, which promised to be applicable to the higher-dimensional matrices encountered in industrial applications, is flawed; a version of such a test previously developed for matrix spectral factorization is shown to be correct, and to differ from the incorrect version in that a condition for the nesting of associated null spaces must also be satisfied. (O.C.)
The inverse Legendre moment transform plays an important role in the field of image analysis applications. In this paper, a recursive algorithm based on Clenshaw's recurrence formula is derived for the fast comput...
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The inverse Legendre moment transform plays an important role in the field of image analysis applications. In this paper, a recursive algorithm based on Clenshaw's recurrence formula is derived for the fast computation of the inverse Legendre moment transform for signal and image reconstruction purposes. The reconstruction can be implemented effectively using recursive equations. The presented algorithm is particularly suitable for parallel very large-scale integrated circuit implementation due to its regular, modular, and simple filter structure.
Motivated by the recent developments in digital diffusion networks, this work is devoted to the rates of convergence issue for a class of global optimization algorithms. By means of weak convergence methods, we show t...
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Motivated by the recent developments in digital diffusion networks, this work is devoted to the rates of convergence issue for a class of global optimization algorithms. By means of weak convergence methods, we show that a sequence of suitably scaled estimation errors converges weakly to a diffusion process (a solution of a stochastic differential equation). The scaling together with the stationary covariance of the limit diffusion process gives the desired rates of convergence. Application examples are also provided for some image estimation problems.
The principal component analysis is to recursively estimate the eigenvectors and the corresponding eigenvalues of a symmetric matrix A based on its noisy observations A(k) = A + N-k, where A is allowed to have arbitra...
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The principal component analysis is to recursively estimate the eigenvectors and the corresponding eigenvalues of a symmetric matrix A based on its noisy observations A(k) = A + N-k, where A is allowed to have arbitrary eigenvalues with multiplicity possibly bigger than one. In the paper the recursive algorithms are proposed and their ordered convergence is established: It is shown that the first algorithm as. converges to a unit eigenvector corresponding to the largest eigenvalue, the second algorithm as. converges to a unit eigenvector corresponding to either the second largest eigenvalue in the case the largest eigenvalue is of single multiplicity or the largest eigenvalue if the multiplicity of the largest eigenvalue is bigger than one, and so on. The convergence rate is also derived. (C) 2011 Elsevier Inc. All rights reserved.
To numerically solve a system of linear algebraic equations with a tridiagonal matrix, a recursive version of Cramer's rule is proposed. This method requires no additional restrictions on the matrix of the system ...
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To numerically solve a system of linear algebraic equations with a tridiagonal matrix, a recursive version of Cramer's rule is proposed. This method requires no additional restrictions on the matrix of the system similar to those formulated for the double-sweep method. The results of numerical experiments on a large set of test problems are presented. A comparative analysis of the efficiency of the method and corresponding algorithms is given.
This paper discusses the adaptive modelling algorithm of the non-linear Errors-in-Variables (EIV) system. The non-linear EIV model is designed as a Wiener model with noisy input and noisy output measurements. The mode...
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This paper discusses the adaptive modelling algorithm of the non-linear Errors-in-Variables (EIV) system. The non-linear EIV model is designed as a Wiener model with noisy input and noisy output measurements. The model consists of a moving average model linear subsystem and a piece-wise linear function as the non-linear subsystem. In order to ensure the online real-time updating of system parameters, the recursive form is designed for the algorithm to keep its adaptive properties and improve the parameters' identification efficiency. The derivation process of the algorithm ensures the recursive calculation results converge to their corresponding true values. The validity and convergence of the algorithm is confirmed by a simulation experiment with the help of Matlab.
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